L47- AWS Services Deep Dive | Lambda Serverless. API Gateway. Bedrock Model Catalog & Playgroun

Lecture 47 of the Gen AI Hindi series — Bipin Kumar walks through every major AWS service you need for GenAI apps, explains serverless vs server with a real analogy, and gives a live tour of Amazon Bedrock's model catalog and playground. --- ### 🧠 What's Covered: **Key AWS Services for GenAI:** - S3 — file and object storage, buckets for any data type - EC2 — rent virtual machines in any size (RAM, CPU, GPU) - SageMaker — ML-focused machines with AI libraries pre-installed, managed Jupyter notebooks - Lambda — serverless compute, pay only when your code runs - API Gateway — authentication, throttling, security layer for your app - Bedrock — host and access 105+ LLM models without managing servers **Lambda vs EC2 — Serverless explained:** EC2 is like renting a car — you pay whether you drive it or not. Lambda is like paying per kilometre — charged only when your code actually runs. Lambda also auto-scales automatically as user traffic grows, making it perfect for unpredictable or bursty workloads like document classification. **API Gateway:** Acts as the gatekeeper for your application. Handles authentication (OAuth 2.0, Cognito), controls the number of requests per second (throttling), and provides security. Supports REST API, HTTP API, and WebSocket (for real-time two-way communication like chatbots). **Amazon Bedrock — Model Catalog:** Serverless models (105+) — no installation needed, pay per token. Used 99% of the time. Marketplace models (150+) — installed like an app on a machine, fixed cost. Better for dedicated high-traffic use. Available providers: Anthropic (Claude), Amazon Nova, OpenAI (GPT), Meta (Llama), Google (Gemma), DeepSeek, Mistral, Qwen, and more. **Data privacy note:** Serverless LLM providers may log your queries to improve their models. For sensitive company data, self-host an open-source model on EC2 via HuggingFace for full data control. **Bedrock Playground:** Test any model directly in the AWS console before writing any code. Check token counts with the built-in tokenizer tool. Compare model pricing per million tokens across providers. --- ### ⏭️ Next: 👉 Lecture 48 — Hands-on AWS project: Document Classifier deployed on Bedrock --- 💬 Questions in the comments — Bipin replies! 📌 Subscribe so you don't miss the hands-on AWS project. --- **#AWSBedrock #Lambda #Serverless #APIGateway #EC2 #S3 #SageMaker #GenAI #AIHindi #BipinKumar #AWSInHindi #ModelCatalog #CloudComputing #GenAIHindi**